Information processing apparatus, line noise reduction processing method, and computer-readable storage medium

ABSTRACT

An information processing apparatus performs first filter processing to combine pixels of an image along a predetermined direction. A line noise image is extracted by executing second filter processing for the processed image along a direction different from the predetermined direction. The extracted line noise image is subtracted from the image to acquire a line noise reduced image.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates to an information processing apparatus,line noise reduction processing method, and computer-readable storagemedium.

2. Description of the Related Art

Diagnoses and treatments based on (moving image) imaging using radiation(for example, X-rays) have been brisk. Recently, an X-ray imagingapparatus using a flat panel detector (in which an amorphous silicon TFTand a semiconductor sensor are formed on a glass substrate) isespecially often used. However, the flat panel detector that uses anamorphous silicon TFT cannot amplify a photoelectrically convertedsignal in a pixel. Instead, accumulated charges are read out via a longsignal line. For this reason, noise is readily generated in an image dueto the influence of external or internal factors.

Imaging using radiation needs to be done in a low dose to reduceradiation exposure of a human body. Hence, a read signal has a verysmall value, and only a slight fluctuation in an image is visuallyrecognized. Particularly, stripe-shaped unevenness (to be referred to asline noise hereinafter) running in the vertical or horizontal directiongreatly influences a diagnostic image because it is sensitively detectedby the human eye.

Conventionally, a technique disclosed in Japanese Patent Laid-Open No.2003-204955 (to be referred to as reference 1 hereinafter) is known as aline noise reduction method. The method of reference 1 performshigh-pass filter processing of an original image containing line noisein a direction perpendicular to the line noise. The processed image thenundergoes low-pass filter processing in the horizontal direction. A linenoise image is consequently acquired. The line noise image is subtractedfrom the original image. This allows to reduce the line noise.

The method of reference 1 uses a low-pass filter to remove an objectextracted by a high-pass filter. In this case, however, object removalis insufficient, resulting in an edge blur or artifact in the object.

Furthermore, the techniques of reference 1 needs filter processing ofall pixels. Since image processing takes time, these methods are notsuitable for, for example, a moving image in fluorography.

SUMMARY OF THE INVENTION

The present invention provides a technique capable of quickly andefficiently removing line noise without any influence of random noise oran object.

According to a first aspect of the present invention there is providedan information processing apparatus comprising: a processing unitconfigured to perform first filter processing to combine pixels of animage along a predetermined direction; an extraction unit configured toextract a line noise image by executing second filter processing for theprocessed image along a direction different from the predetermineddirection; and a difference processing unit configured to subtract, fromthe image, the line noise image extracted by the extraction unit so asto acquire a line noise reduced image.

According to a second aspect of the present invention there is provideda line noise reduction processing method of an information processingapparatus, comprising: performing first filter processing to combinepixels of an image along a predetermined direction; extracting a linenoise image by executing second filter processing for the processedimage along a direction different from the predetermined direction; andsubtracting, from the image, the line noise image extracted by theextraction unit so as to acquire a line noise reduced image.

According to a third aspect of the present invention there is provided acomputer-readable storage medium storing a program which causes acomputer to function as: a processing unit configured to perform firstfilter processing to combine pixels of an image along a predetermineddirection; an extraction unit configured to extract a line noise imageby executing second filter processing for the processed image along adirection different from the predetermined direction; and a differenceprocessing unit configured to subtract, from the image, the line noiseimage extracted by the extraction unit so as to acquire a line noisereduced image.

Further features of the present invention will be apparent from thefollowing description of exemplary embodiments with reference to theattached drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram showing an example of the functionalarrangement of an information processing apparatus according to anembodiment of the present invention;

FIG. 2 is a view showing an outline of line noise removal processingaccording to the embodiment;

FIG. 3 is a flowchart illustrating an example of the procedure of linenoise reduction processing;

FIG. 4 is a graph showing an example of a line noise reduction effectaccording to the embodiment; and

FIGS. 5A and 5B are graphs showing an example of a line noise reductioneffect according to the embodiment.

DESCRIPTION OF THE EMBODIMENTS

An exemplary embodiment(s) of the present invention will now bedescribed in detail with reference to the drawings. It should be notedthat the relative arrangement of the components, the numericalexpressions and numerical values set forth in these embodiments do notlimit the scope of the present invention unless it is specificallystated otherwise.

FIG. 1 is a block diagram showing an example of the functionalarrangement of an information processing apparatus according to anembodiment of the present invention.

An information processing apparatus 10 includes one or a plurality ofcomputers. The computer includes, for example, a main control unit suchas a CPU, and storage units such as a ROM (Read Only Memory) and a RAM(Random Access Memory). The computer may also include a communicationunit such as a network card, and input/output units such as a keyboardand a display or a touch panel. Note that these constituent units areconnected via a bus or the like and controlled by causing the maincontrol unit to execute programs stored in the storage unit.

The information processing apparatus 10 includes, as functionalcomponents, an image input unit 21, reduction processing unit 22,extraction unit 27, threshold processing unit 24, interpolationprocessing unit 25, difference processing unit 26, calculation unit 28,and holding unit 29.

The image input unit 21 externally inputs an image (to be referred to asan input image hereinafter). An input image 30 is a two-dimensionalimage formed from, for example, n horizontal pixels x m vertical pixels.The input image 30 according to this embodiment contains an object andline noise in a predetermined direction (stripe-shaped unevennessrunning in the vertical or horizontal direction), as indicated by 41 inFIG. 2. Note that in this embodiment, the predetermined direction is thehorizontal direction, and an example in which line noise appears in thehorizontal direction will be described. However, the predetermineddirection may be the vertical direction, as a matter of course. Thetwo-dimensional image is obtained by X-rays. However, the image need notalways be obtained by X-rays.

The reduction processing unit 22 reduces the input image 30 in apredetermined direction (the same direction as that of line noise)(first filter processing). More specifically, the pixels in the image(input image 30) are linearly combined along the predetermined direction(the horizontal direction in this embodiment). Note that the unit of thenumber of pixels to be combined by linear combination is held in theholding unit 29. The reduction processing unit 22 performs linearcombination based on the value held in the holding unit 29. In thelinear combination, the input image 30 is reduced in the horizontaldirection by using, for example, the average value of k (k≧2) pixels asthe value of one pixel. With this processing, a horizontally reducedimage indicated by 42 in FIG. 2 is obtained. The reduction processing isnot limited to the above-described method, and a generally known methodmay be used. Note that the number of pixels to be combined need notalways be uniform. Since the reduction processing suppresses randomnoise, it is possible to efficiently perform line noise componentextraction (edge-exclusion high-pass filter processing). The number ofpixels that undergo the filter processing decreases to n/k. This allowsto shorten the processing time of the extraction unit 27 of thesucceeding stage.

The extraction unit 27 extracts a line noise (image) 32 from a reducedimage 31. The extraction unit 27 includes a filter processing unit 23,the threshold processing unit 24, and the interpolation processing unit25. The filter processing unit 23 performs, for example, edge-exclusionhigh-pass filter processing (second filter processing) for the imagereduced by the reduction processing unit 22, thereby extracting linenoise. The edge-exclusion high-pass filter processing is performed in adirection (the vertical direction in this embodiment) perpendicular tothe direction in which the line noise appears. Note that the filterprocessing need not always be done in the perpendicular direction. Morespecifically, the direction need not accurately be perpendicular to thedirection in which the line noise appears, and the filter processing isperformed along a direction with a margin in a predetermined range. Withthis filter processing, the line noise image 32 as indicated by 43 inFIG. 2 is obtained by removing the object from the reduced image 31.Note that the edge-exclusion high-pass filter according to thisembodiment indicates a nonlinear high-pass filter which changes thecoefficients depending on data and makes it difficult to extract anedge. For example, there is a filter such as an ε filter whose filtercoefficients change depending on data. An edge-exclusion high-pass εfilter can be represented by

$\begin{matrix}{{{Iout}()} = {\sum\limits_{j = {- h}}^{h}\; {\frac{1}{r\sqrt{\pi}}{\exp \left( {- \frac{j^{2}}{r^{2}}} \right)}{F\left( {{I()} - {I\left( { + j} \right)}} \right)}}}} & (1)\end{matrix}$

for

F(p)=p for |p|<ε

F(p)=0 for |p|≧ε

where I(i) is a pixel value before filter processing, Iout(i) is a pixelvalue after filter processing, r is the Gaussian radius that determinesthe frequency characteristic of the filter, and h is the order of thefilter.

As described above, the ε filter is a data-dependent filter. As itscharacteristic feature, if the difference between the pixel of interestand a neighboring pixel is larger than ε, the filter coefficient for theneighboring pixel is made small. This allows to remove a contrast signalequal to or more than the ε value. Note that, for example, a dispersivefilter, MTM filter, and bilateral filter are also known asdata-dependent filters. An edge-exclusion high-pass filter may be formedusing these filters.

The threshold processing unit 24 executes threshold processing for theline noise image 32 in a predetermined direction (the same direction asthat of line noise). The line noise has strong correlation in thehorizontal direction. Hence, the threshold processing unit 24 comparesthe pixels in the horizontal direction. If one of pixels arranged in thehorizontal direction exhibits a prominent value, the pixel is not a linenoise component at a high probability (for example, object). Hence, thepixel is removed. More specifically, the threshold processing unit 24obtains the standard deviation and average value of the pixels in thehorizontal direction. A pixel deviated from the average value by thestandard deviation or more (beyond a predetermined threshold) isdetermined to be the object and removed from the line noise image 32.With this processing, a line noise image (after threshold processing) 33is obtained by more accurate object removal.

The interpolation processing unit 25 executes pixel interpolationprocessing for the line noise image (after threshold processing) 33.That is, the interpolation processing unit 25 interpolates pixels lostby the processing of the threshold processing unit 24. The line noisehas strong correlation in the horizontal direction. Hence, interpolationis performed using, for example, adjacent pixels in the horizontaldirection. With this processing, a line noise image (after interpolationprocessing) 34 as indicated by 43 in FIG. 2 is obtained.

The difference processing unit 26 calculates the difference between theinput image 30 and the line noise image (after interpolation processing)34. More specifically, the difference processing unit 26 subtracts theline noise image (after interpolation processing) 34 indicated by 43 inFIG. 2 from the input image 30 indicated by 41 in FIG. 2. With thisprocessing, a line noise reduced image 35 indicated by 44 in FIG. 2 isacquired. The line noise image (after interpolation processing) 34 forthe difference processing has been reduced in the horizontal direction.However, since the line noise has strong correlation in the horizontaldirection, as described above, no problem particularly arises concerningthe accuracy of subtraction processing when corresponding pixels aresubtracted from the pixels of the input image 30 used for reduction.

Alternatively, the above-described difference processing may beperformed after enlarging the reduced image to the size of the inputimage 30 using generally known interpolation, that is, approximation. Ifthe input image 30 includes regions segmented by pattern recognition orobject recognition, and each region has corresponding attributeinformation, the weight in line noise image subtraction may be changedin accordance with the information. For example, the weight is set to1.0 for a region outside the irradiation field or a non-object portionand to 0.7 for an object portion. This enables to decrease errors in theimage even if the object is erroneously extracted upon creating the linenoise image.

The calculation unit 28 calculates the number of pixels to be combinedin linear combination (by the reduction processing unit 22). Thecalculation unit 28 calculates the number of pixels based on randomnoise standard deviation and line noise standard deviation. Note thatthe calculation processing will be described later in detail. Theholding unit 29 holds the calculated value. The calculation processingby the calculation unit 28 is performed in, for example, initialsetting, device calibration, or the like. In subsequent processing,linear combination is done based on the value held in the holding unit29 in advance. Note that a serviceman or the like may input a solid linenoise image in initial setting or device calibration, and analyze theoutput result to determine the optimum number of linear combinationpixels. In this case, the holding unit 29 holds a value input by theserviceman or the like.

An example of the procedure of line noise reduction processing in theinformation processing apparatus 10 shown in FIG. 1 will be describedwith reference to FIG. 3.

The information processing apparatus 10 causes the image input unit 21to externally input the image (input image) 30 (S101), thereby startingthe processing. Note that image input can be done via a network or thelike or via a storage medium such as a memory card. The method is notparticularly limited.

When the image is input, the information processing apparatus 10 causesthe reduction processing unit 22 to reduce the input image 30 in thehorizontal direction (S102). As described above, for example, theaverage value of k pixels is defined as the value of one pixel, therebyreducing the input image 30 in the horizontal direction. As a result,the input image 30 is reduced to, for example, n/k in the horizontaldirection. Random noise (noise in each pixel) representing the degree ofvariation in each pixel is reduced to 1/√/k. Line noise componentshaving strong correlation in the horizontal direction are preserved.

Next, the information processing apparatus 10 causes the filterprocessing unit 23 to execute filter processing, thereby extracting theline noise (image) 32 from the obtained reduced image 31 (S103). Theinformation processing apparatus 10 then causes the threshold processingunit 24 to execute threshold processing in the horizontal direction forthe extracted line noise image 32 (S104).

After that, the information processing apparatus 10 causes theinterpolation processing unit 25 to perform interpolation processing forthe line noise image (after threshold processing) 33 (S105). That is,pixels removed from the line noise image by the processing in step S104are interpolated. After the interpolation processing, the informationprocessing apparatus 10 causes the difference processing unit 26 tocalculate the difference between the input image 30 input in step S101and the line noise image (after interpolation processing) 34. With thisprocessing, the line noise reduced image 35 is obtained by subtractingthe line noise from the input image 30.

Note that the procedure of the noise reduction processing shown in FIG.3 is merely an example. The processing is appropriately changed inaccordance with the process target image. For example, the thresholdprocessing in step S104 or the interpolation processing in step S105need not always be executed, and may be omitted.

An example of a line noise reduction effect obtained by executing thehorizontal reduction processing (S102 in FIG. 3) will be described nextwith reference to FIG. 4.

FIG. 4 is a graph illustrating an example of the relationship betweenthe noise detection state and the number of combined pixels. Theabscissa of the graph represents the unit of the number of pixelslinearly combined by the horizontal reduction processing of thereduction processing unit 22. The ordinate represents a value (to bereferred to as a random/line ratio hereinafter) obtained by dividingrandom noise standard deviation by line noise standard deviation. Therandom noise standard deviation is the standard deviation of each pixelin the line noise reduced image. The line noise standard deviation is aresult obtained by, for example, combining the pixels in the horizontaldirection by the above-described reduction processing, averaging thepixel values, and calculating the standard deviation in the verticaldirection.

From the results of past subjective evaluation experiments, the linenoise in the input image 30 is hardly visually recognized when therandom/line ratio is 7 or more and, more preferably, 10 or more. Asshown in FIG. 4, the random/line ratio is about 4 in an image(corresponding to the input image 30) which has not undergone noisereduction (“without processing” on the abscissa in FIG. 4). In an imagewhich has undergone noise reduction processing without linearcombination of pixels (“without combination” on the abscissa in FIG. 4),as in the prior art, the random/line ratio is about 6.

However, when the reduction processing unit 22 is provided to linearlycombine pixels, and the resultant image (corresponding to the reducedimage 31) undergoes the above-described noise reduction processing (“4to 1104 pixels” on the abscissa in FIG. 4), as in this embodiment, avalue larger than 7 is obtained as the random/line ratio. When thenumber of pixels to be combined in linear combination is adjusted inaccordance with the uniformity and level of line noise, a value largerthan 10 is obtained as the random/line ratio (for example, “8 pixels”and “23 pixels” on the abscissa in FIG. 4).

The edge of the object after the line noise reduction processingaccording to this embodiment will be described next with reference toFIGS. 5A and 5B.

FIGS. 5A and 5B are graphs showing examples of vertical pixel positionsand pixel values before and after the line noise reduction processing.For easier understanding of the effect of line noise reductionprocessing according to this embodiment, FIG. 5A shows vertical pixelpositions and pixel values before and after the line noise reductionprocessing according to this embodiment, and FIG. 5B shows those in theconventional method.

The abscissa of each graph represents the vertical pixel position, andthe ordinate represents the pixel value of the pixel.

Executing line noise reduction processing by the conventional methodequals applying a low-pass filter in the vertical direction, resultingin an edge blur of the object, as shown in FIG. 5B. On the other hand,in this embodiment, the object and its edge portion are removed using anedge-exclusion high-pass filter to extract line noise. Hence, line noisecan be reduced while ensuring the edge, as shown in FIG. 5A.

As described above, according to this embodiment, the pixels arelinearly combined in the direction in which line noise runs. After that,filter processing is performed using an edge-exclusion high-pass filter.This makes it possible to more effectively reduce line noise than in theconventional method and suppress an artifact or edge blur in theprocessed image. Additionally, since filter processing is performed fora reduced image, the processing time can shorten. Furthermore, a movingimage can undergo the processing with less processing load than before.

More specifically, according to this embodiment, it is possible toextract line noise without any influence of random noise or an object.This enables to reduce line noise and suppress an artifact or edge blurin an image as compared to a case in which the arrangement is notadopted. In addition, since filter processing is performed for a reducedimage, the processing time can shorten.

A typical embodiment of the present invention has been described above.However, the present invention is not limited to the above-described andillustrated embodiment, and various changes and modifications canappropriately be made within the spirit and scope of the presentinvention.

For example, the present invention can take a form of, for example, asystem, apparatus, method, program, or computer-readable storage medium.More specifically, the present invention is applicable to a systemincluding a plurality of devices, or an apparatus including a singledevice.

Other Embodiments

Aspects of the present invention can also be realized by a computer of asystem or apparatus (or devices such as a CPU or MPU) that reads out andexecutes a program recorded on a memory device to perform the functionsof the above-described embodiment(s), and by a method, the steps ofwhich are performed by a computer of a system or apparatus by, forexample, reading out and executing a program recorded on a memory deviceto perform the functions of the above-described embodiment(s). For thispurpose, the program is provided to the computer for example via anetwork or from a recording medium of various types serving as thememory device (for example, computer-readable storage medium).

While the present invention has been described with reference toexemplary embodiments, it is to be understood that the invention is notlimited to the disclosed exemplary embodiments. The scope of thefollowing claims is to be accorded the broadest interpretation so as toencompass all such modifications and equivalent structures andfunctions.

This application claims the benefit of Japanese Patent Application No.2009-174742 filed on Jul. 27, 2009, which is hereby incorporated byreference herein in its entirety.

1. An information processing apparatus for a radiation image comprising:a processing unit configured to perform averaging of pixels of aradiation image along a specific direction; an extraction unitconfigured to extract line noise data from the processed radiation imagealong a direction different from the specific direction; and adifference processing unit configured to obtain a line noise reducedimage based on the radiation image and the line noise data.
 2. Theapparatus according to claim 1, wherein said extraction unit comprises:a threshold processing unit configured to execute threshold processingfor the extracted line noise data so as to remove, from the line noisedata, a pixel whose value exceeds a predetermined threshold out of thepixels; and an interpolation processing unit configured to executeinterpolation processing for a region of the removed pixel in the linenoise data processed by said threshold processing unit.
 3. The apparatusaccording to claim 2, wherein interpolation processing is performed tomake a size of the extracted line noise data match with that of theradiation image.
 4. The apparatus according to claim 1, wherein theradiation image has attribute information corresponding to each regionin the radiation image, and said difference processing unit obtains theline noise reduced image based on a weight based on the attributeinformation.
 5. An apparatus according to claim 1, wherein theprocessing unit is configured to perform linear combination of pixelsalong the specific direction.
 6. The apparatus according to claim 5,further comprising a holding unit configured to hold, in advance, thenumber of pixels for linear combination based on random noise standarddeviation of each pixel in the line noise reduced image and line noisestandard deviation calculated, along the direction different from thespecific direction, from the line noise data extracted by saidextraction unit, wherein said processing unit performs the linearcombination along the specific direction based on the number of pixelsheld in said holding unit.
 7. The apparatus according to claim 6,wherein the number of pixels for linear combination is determined to avalue at which a value obtained by dividing the random noise standarddeviation by the line noise standard deviation is not less than
 7. 8.The apparatus according to claim 1, wherein the extraction unit extractsthe line noise data by performing a filter processing in a directionperpendicular to the specific direction using an edge-exclusionhigh-pass filter formed from one of an ε filter, a dispersive filter, anMTM filter, and a bilateral filter.
 9. A line noise reduction processingmethod of an information processing apparatus, comprising: performingaveraging of pixels of a radiation image along a specific direction;extracting a line noise data from the processed radiation image along adirection different from the specific direction; and obtaining, a linenoise reduced image based on the radiation image and the line noisedata.
 10. A computer-readable storage medium storing a program whichcauses a computer to function as: a processing unit configured toperform averaging of pixels of a radiation image along a specificdirection; an extraction unit configured to extract a line noise datafrom the processed radiation image along a direction different from thespecific direction; and a difference processing unit configured toobtain a line noise reduced image based on the radiation image and theline noise data.